Meet the Scientists on the Frontlines of Protecting Humanity from a Man-Made Pathogen
Jean Peccoud wasn't expecting an email from the FBI. He definitely wasn't expecting the agency to invite him to a meeting. "My reaction was, 'What did I do wrong to be on the FBI watch list?'" he recalls.
You use those blueprints for white-hat research—which is, indeed, why the open blueprints exist—or you can do the same for a black-hat attack.
He didn't know what the feds could possibly want from him. "I was mostly scared at this point," he says. "I was deeply disturbed by the whole thing."
But he decided to go anyway, and when he traveled to San Francisco for the 2008 gathering, the reason for the e-vite became clear: The FBI was reaching out to researchers like him—scientists interested in synthetic biology—in anticipation of the potential nefarious uses of this technology. "The whole purpose of the meeting was, 'Let's start talking to each other before we actually need to talk to each other,'" says Peccoud, now a professor of chemical and biological engineering at Colorado State University. "'And let's make sure next time you get an email from the FBI, you don't freak out."
Synthetic biology—which Peccoud defines as "the application of engineering methods to biological systems"—holds great power, and with that (as always) comes great responsibility. When you can synthesize genetic material in a lab, you can create new ways of diagnosing and treating people, and even new food ingredients. But you can also "print" the genetic sequence of a virus or virulent bacterium.
And while it's not easy, it's also not as hard as it could be, in part because dangerous sequences have publicly available blueprints. You use those blueprints for white-hat research—which is, indeed, why the open blueprints exist—or you can do the same for a black-hat attack. You could synthesize a dangerous pathogen's code on purpose, or you could unwittingly do so because someone tampered with your digital instructions. Ordering synthetic genes for viral sequences, says Peccoud, would likely be more difficult today than it was a decade ago.
"There is more awareness of the industry, and they are taking this more seriously," he says. "There is no specific regulation, though."
Trying to lock down the interconnected machines that enable synthetic biology, secure its lab processes, and keep dangerous pathogens out of the hands of bad actors is part of a relatively new field: cyberbiosecurity, whose name Peccoud and colleagues introduced in a 2018 paper.
Biological threats feel especially acute right now, during the ongoing pandemic. COVID-19 is a natural pathogen -- not one engineered in a lab. But future outbreaks could start from a bug nature didn't build, if the wrong people get ahold of the right genetic sequences, and put them in the right sequence. Securing the equipment and processes that make synthetic biology possible -- so that doesn't happen -- is part of why the field of cyberbiosecurity was born.
The Origin Story
It is perhaps no coincidence that the FBI pinged Peccoud when it did: soon after a journalist ordered a sequence of smallpox DNA and wrote, for The Guardian, about how easy it was. "That was not good press for anybody," says Peccoud. Previously, in 2002, the Pentagon had funded SUNY Stonybrook researchers to try something similar: They ordered bits of polio DNA piecemeal and, over the course of three years, strung them together.
Although many years have passed since those early gotchas, the current patchwork of regulations still wouldn't necessarily prevent someone from pulling similar tricks now, and the technological systems that synthetic biology runs on are more intertwined — and so perhaps more hackable — than ever. Researchers like Peccoud are working to bring awareness to those potential problems, to promote accountability, and to provide early-detection tools that would catch the whiff of a rotten act before it became one.
Peccoud notes that if someone wants to get access to a specific pathogen, it is probably easier to collect it from the environment or take it from a biodefense lab than to whip it up synthetically. "However, people could use genetic databases to design a system that combines different genes in a way that would make them dangerous together without each of the components being dangerous on its own," he says. "This would be much more difficult to detect."
After his meeting with the FBI, Peccoud grew more interested in these sorts of security questions. So he was paying attention when, in 2010, the Department of Health and Human Services — now helping manage the response to COVID-19 — created guidance for how to screen synthetic biology orders, to make sure suppliers didn't accidentally send bad actors the sequences that make up bad genomes.
Guidance is nice, Peccoud thought, but it's just words. He wanted to turn those words into action: into a computer program. "I didn't know if it was something you can run on a desktop or if you need a supercomputer to run it," he says. So, one summer, he tasked a team of student researchers with poring over the sentences and turning them into scripts. "I let the FBI know," he says, having both learned his lesson and wanting to get in on the game.
Peccoud later joined forces with Randall Murch, a former FBI agent and current Virginia Tech professor, and a team of colleagues from both Virginia Tech and the University of Nebraska-Lincoln, on a prototype project for the Department of Defense. They went into a lab at the University of Nebraska at Lincoln and assessed all its cyberbio-vulnerabilities. The lab develops and produces prototype vaccines, therapeutics, and prophylactic components — exactly the kind of place that you always, and especially right now, want to keep secure.
"We were creating wiki of all these nasty things."
The team found dozens of Achilles' heels, and put them in a private report. Not long after that project, the two and their colleagues wrote the paper that first used the term "cyberbiosecurity." A second paper, led by Murch, came out five months later and provided a proposed definition and more comprehensive perspective on cyberbiosecurity. But although it's now a buzzword, it's the definition, not the jargon, that matters. "Frankly, I don't really care if they call it cyberbiosecurity," says Murch. Call it what you want: Just pay attention to its tenets.
A Database of Scary Sequences
Peccoud and Murch, of course, aren't the only ones working to screen sequences and secure devices. At the nonprofit Battelle Memorial Institute in Columbus, Ohio, for instance, scientists are working on solutions that balance the openness inherent to science and the closure that can stop bad stuff. "There's a challenge there that you want to enable research but you want to make sure that what people are ordering is safe," says the organization's Neeraj Rao.
Rao can't talk about the work Battelle does for the spy agency IARPA, the Intelligence Advanced Research Projects Activity, on a project called Fun GCAT, which aims to use computational tools to deep-screen gene-sequence orders to see if they pose a threat. It can, though, talk about a twin-type internal project: ThreatSEQ (pronounced, of course, "threat seek").
The project started when "a government customer" (as usual, no one will say which) asked Battelle to curate a list of dangerous toxins and pathogens, and their genetic sequences. The researchers even started tagging sequences according to their function — like whether a particular sequence is involved in a germ's virulence or toxicity. That helps if someone is trying to use synthetic biology not to gin up a yawn-inducing old bug but to engineer a totally new one. "How do you essentially predict what the function of a novel sequence is?" says Rao. You look at what other, similar bits of code do.
"We were creating wiki of all these nasty things," says Rao. As they were working, they realized that DNA manufacturers could potentially scan in sequences that people ordered, run them against the database, and see if anything scary matched up. Kind of like that plagiarism software your college professors used.
Battelle began offering their screening capability, as ThreatSEQ. When customers -- like, currently, Twist Bioscience -- throw their sequences in, and get a report back, the manufacturers make the final decision about whether to fulfill a flagged order — whether, in the analogy, to give an F for plagiarism. After all, legitimate researchers do legitimately need to have DNA from legitimately bad organisms.
"Maybe it's the CDC," says Rao. "If things check out, oftentimes [the manufacturers] will fulfill the order." If it's your aggrieved uncle seeking the virulent pathogen, maybe not. But ultimately, no one is stopping the manufacturers from doing so.
Beyond that kind of tampering, though, cyberbiosecurity also includes keeping a lockdown on the machines that make the genetic sequences. "Somebody now doesn't need physical access to infrastructure to tamper with it," says Rao. So it needs the same cyber protections as other internet-connected devices.
Scientists are also now using DNA to store data — encoding information in its bases, rather than into a hard drive. To download the data, you sequence the DNA and read it back into a computer. But if you think like a bad guy, you'd realize that a bad guy could then, for instance, insert a computer virus into the genetic code, and when the researcher went to nab her data, her desktop would crash or infect the others on the network.
Something like that actually happened in 2017 at the USENIX security symposium, an annual programming conference: Researchers from the University of Washington encoded malware into DNA, and when the gene sequencer assembled the DNA, it corrupted the sequencer's software, then the computer that controlled it.
"This vulnerability could be just the opening an adversary needs to compromise an organization's systems," Inspirion Biosciences' J. Craig Reed and Nicolas Dunaway wrote in a paper for Frontiers in Bioengineering and Biotechnology, included in an e-book that Murch edited called Mapping the Cyberbiosecurity Enterprise.
Where We Go From Here
So what to do about all this? That's hard to say, in part because we don't know how big a current problem any of it poses. As noted in Mapping the Cyberbiosecurity Enterprise, "Information about private sector infrastructure vulnerabilities or data breaches is protected from public release by the Protected Critical Infrastructure Information (PCII) Program," if the privateers share the information with the government. "Government sector vulnerabilities or data breaches," meanwhile, "are rarely shared with the public."
"What I think is encouraging right now is the fact that we're even having this discussion."
The regulations that could rein in problems aren't as robust as many would like them to be, and much good behavior is technically voluntary — although guidelines and best practices do exist from organizations like the International Gene Synthesis Consortium and the National Institute of Standards and Technology.
Rao thinks it would be smart if grant-giving agencies like the National Institutes of Health and the National Science Foundation required any scientists who took their money to work with manufacturing companies that screen sequences. But he also still thinks we're on our way to being ahead of the curve, in terms of preventing print-your-own bioproblems: "What I think is encouraging right now is the fact that we're even having this discussion," says Rao.
Peccoud, for his part, has worked to keep such conversations going, including by doing training for the FBI and planning a workshop for students in which they imagine and work to guard against the malicious use of their research. But actually, Peccoud believes that human error, flawed lab processes, and mislabeled samples might be bigger threats than the outside ones. "Way too often, I think that people think of security as, 'Oh, there is a bad guy going after me,' and the main thing you should be worried about is yourself and errors," he says.
Murch thinks we're only at the beginning of understanding where our weak points are, and how many times they've been bruised. Decreasing those contusions, though, won't just take more secure systems. "The answer won't be technical only," he says. It'll be social, political, policy-related, and economic — a cultural revolution all its own.
Two-and-a-half year-old Huckleberry, a blue merle Australian shepherd, pulls hard at her leash; her yelps can be heard by skiers and boarders high above on the chairlift that carries them over the ski patrol hut to the top of the mountain. Huckleberry is an avalanche rescue dog — or avy dog, for short. She lives and works with her owner and handler, a ski patroller at Breckenridge Ski Resort in Colorado. As she watches the trainer play a game of hide-and-seek with six-month-old Lume, a golden retriever and avy dog-in-training, Huckleberry continues to strain on her leash; she loves the game. Hide-and-seek is one of the key training methods for teaching avy dogs the rescue skills they need to find someone caught in an avalanche — skier, snowmobiler, hiker, climber.
Lume’s owner waves a T-shirt in front of the puppy. While another patroller holds him back, Lume’s owner runs away and hides. About a minute later — after a lot of barking — Lume is released and commanded to “search.” He springs free, running around the hut to find his owner who reacts with a great amount of excitement and fanfare. Lume’s scent training will continue for the rest of the ski season (Breckenridge plans operating through May or as long as weather permits) and through the off-season. “We make this game progressively harder by not allowing the dog watch the victim run away,” explains Dave Leffler, Breckenridge's ski patroller and head of the avy dog program, who has owned, trained and raised many of them. Eventually, the trainers “dig an open hole in the snow to duck out of sight and gradually turn the hole into a cave where the dog has to dig to get the victim,” explains Leffler.
By the time he is three, Lume, like Huckleberry, will be a fully trained avy pup and will join seven other avy dogs on Breckenridge ski patrol team. Some of the team members, both human and canine, are also certified to work with Colorado Rapid Avalanche Deployment, a coordinated response team that works with the Summit County Sheriff’s office for avalanche emergencies outside of the ski slopes’ boundaries.
There have been 19 avalanche deaths in the U.S. this season, according to avalanche.org, which tracks slides; eight in Colorado. During the entirety of last season there were 17. Avalanche season runs from November through June, but avalanches can occur year-round.
High tech and high stakes
Complementing avy dogs’ ability to smell people buried in a slide, avalanche detection, rescue and recovery is becoming increasingly high tech. There are transceivers, signal locators, ground scanners and drones, which are considered “games changers” by many in avalanche rescue and recovery
For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
A drone can provide thermal imaging of objects caught in a slide; what looks like a rock from far away might be a human with a heat signature. Transceivers, also known as beacons, send a signal from an avalanche victim to a companion. Signal locators, like RECCO reflectors which are often sewn directly into gear, can echo back a radar signal sent by a detector; most ski resorts have RECCO detector units.
Research suggests that Ground Penetrating Radar (GPR), an electromagnetic tool used by geophysicists to pull images from inside the ground, could be used to locate an avalanche victim. A new study from the Department of Energy’s Sandia National Laboratories suggests that a computer program developed to pinpoint the source of a chemical or biological terrorist attack could also be used to find someone submerged in an avalanche. The search algorithm allows for small robots (described as cockroach-sized) to “swarm” a search area. Researchers say that this distributed optimization algorithm can help find avalanche victims four times faster than current search mechanisms. For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
An avy dog in training is picking up scent
Sarah McLear
While rescue gear has been evolving, predicting when a slab will fall remains an emerging science — kind of where weather forecasting science was in the 1980s. Avalanche forecasting still relies on documenting avalanches by going out and looking,” says Ethan Greene, director of the Colorado Avalanche Information Center (CAIC). “So if there's a big snowstorm, and as you might remember, most avalanches happened during snowstorms, we could have 10,000 avalanches that release and we document 50,” says Greene. “Avalanche forecasting is essentially pattern recognition,” he adds--and understanding the layering structure of snow.
However, determining where the hazards lie can be tricky. While a dense layer of snow over a softer, weaker layer may be a recipe for an avalanche, there’s so much variability in snowpack that no one formula can predict the trigger. Further, observing and measuring snow at a single point may not be representative of all nearby slopes. Finally, there’s not enough historical data to help avalanche scientists create better prediction models.
That, however, may be changing.
Last year, an international group of researchers created computer simulations of snow cover using 16 years of meteorological data to forecast avalanche hazards, publishing their research in Cold Regions Science and Technology. They believe their models, which categorize different kinds of avalanches, can support forecasting and determine whether the avalanche is natural (caused by temperature changes, wind, additional snowfall) or artificial (triggered by a human or animal).
With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides.
With data from two sites in British Columbia and one in Switzerland, researchers built computer simulations of five different avalanche types. “In terms of real time avalanche forecasting, this has potential to fill in a lot of data gaps, where we don't have field observations of what the snow looks like,” says Simon Horton, a postdoctoral fellow with the Simon Fraser University Centre for Natural Hazards Research and a forecaster with Avalanche Canada, who participated in the study. While complex models that simulate snowpack layers have been around for a few decades, they weren’t easy to apply until recently. “It's been difficult to find out how to apply that to actual decision-making and improving safety,” says Horton. If you can derive avalanche problem types from simulated snowpack properties, he says, you’ll learn “a lot about how you want to manage that risk.”
The five categories include “new snow,” which is unstable and slides down the slope, “wet snow,” when rain or heat makes it liquidly, as well as “wind-drifted snow,” “persistent weak layers” and “old snow.” “That's when there's some type of deeply buried weak layer in the snow that releases without any real change in the weather,” Horton explains. “These ones tend to cause the most accidents.” One step by a person on that structurally weak layer of snow will cause a slide. Horton is hopeful that computer simulations of avalanche types can be used by scientists in different snow climates to help predict hazard levels.
Greene is doubtful. “If you have six slopes that are lined up next to each other, and you're going to try to predict which one avalanches and the exact dimensions and what time, that's going to be really hard to do. And I think it's going to be a long time before we're able to do that,” says Greene.
What both researchers do agree on, though, is that what avalanche prediction really needs is better imagery through satellite detection. “Just being able to count the number of avalanches that are out there will have a huge impact on what we do,” Greene says. “[Satellites] will change what we do, dramatically.” In a 2022 paper, scientists at the University of Aberdeen in England used satellites to study two deadly Himalayan avalanches. The imaging helped them determine that sediment from a 2016 ice avalanche plus subsequent snow avalanches contributed to the 2021 avalanche that caused a flash flood, killing over 200 people. The researchers say that understanding the avalanches characteristics through satellite imagery can inform them how one such event increases the magnitude of another in the same area.
Avy dogs trainers hide in dug-out holes in the snow, teaching the dogs to find buried victims
Sarah McLear
Lifesaving combo: human tech and Mother Nature’s gear
Even as avalanche forecasting evolves, dogs with their built-in rescue mechanisms will remain invaluable. With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides. (Humans in comparison, have a meager 12 million.) A new study published in the Journal of Neuroscience revealed that in dogs smell and vision are connected in the brain, which has not been found in other animals. “They can detect the smell of their owner's fingerprints on a glass slide six weeks after they touched it,” says Nicholas Dodman, professor emeritus at Cummings School of Veterinary Medicine at Tufts University. “And they can track from a boat where a box filled with meat was buried in the water, 100 feet below,” says Dodman, who is also co-founder and president of the Center for Canine Behavior Studies.
Another recent study from Queens College in Belfast, United Kingdom, further confirms that dogs can smell when humans are stressed. They can also detect the smell of a person’s breath and the smell of the skin cells of a deceased person.
The emerging avalanche-predicting human-made tech and the incredible nature-made tech of dogs’ olfactory talents is the lifesaving “equipment” that Leffler believes in. Even when human-made technology develops further, it will be most efficient when used together with the millions of dogs’ smell receptors, Leffler believes. “It is a combination of technology and the avalanche dog that will always be effective in finding an avalanche victim.”
Living with someone changes your microbiome, new research shows
Some roommate frustration can be expected, whether it’s a sink piled high with crusty dishes or crumbs where a clean tabletop should be. Now, research suggests a less familiar issue: person-to-person transmission of shared bacterial strains in our gut and oral microbiomes. For the first time, the lab of Nicola Segata, a professor of genetics and computational biology at the University of Trento, located in Italy, has shown that bacteria of the microbiome are transmitted between many individuals, not just infants and their mothers, in ways that can’t be explained by their shared diet or geography.
It’s a finding with wide-ranging implications, yet frustratingly few predictable outcomes. Our microbiomes are an ever-growing and changing collection of helpful and harmful bacteria that we begin to accumulate the moment we’re born, but experts are still struggling to unravel why and how bacteria from one person’s gut or mouth become established in another person’s microbiome, as opposed to simply passing through.
“If we are looking at the overall species composition of the microbiome, then there is an effect of age of course, and many other factors,” Segata says. “But if we are looking at where our strains are coming from, 99 percent of them are only present in other people’s guts. They need to come from other guts.”
If we could better understand this process, we might be able to control and use it; perhaps hospital patients could avoid infections from other patients when their microbiome is depleted by antibiotics and their immune system is weakened, for example. But scientists are just beginning to link human microbiomes with various ailments. Growing evidence shows that our microbiomes steer our long-term health, impacting conditions like obesity, irritable bowel syndrome, type 2 diabetes, and cancer.
Previous work from Segata’s lab and others illuminated the ways bacteria are passed from mothers to infants during the first few months of life during vaginal birth, breastfeeding and other close contact. And scientists have long known that people in close proximity tend to share bacteria. But the factors related to that overlap, such as genetics and diet, were unclear, especially outside the mother-baby dyad.
“If we look at strain sharing between a mother and an infant at five years of age, for example, we cannot really tell which was due to transmission at birth and which is due to continued transmission because of contact,” Segata says. Experts hypothesized that they could be caused by bacterial similarities in the environment itself, genetics, or bacteria from shared foods that colonized the guts of people in close contact.
Strain sharing was highest in mother-child pairs, with 96 percent of them sharing strains, and only slightly lower in members of shared households, at 95 percent.
In Italy, researchers led by Mireia Valles-Colomer, including Segata, hoped to unravel this mystery. They compared data from 9,715 stool and saliva samples in 31 genomic datasets with existing metadata. Scientists zoomed in on variations in each bacterial strain down to the individual level. They examined not only mother-child pairs, but people living in the same household, adult twins, and people living in the same village in a level of detail that wasn’t possible before, due to its high cost and difficulties in retrieving data about interactions between individuals, Segata explained.
“This paper is, with high granularity, quantifying the percent sharing that you expect between different types of social interactions, controlling for things like genetics and diet,” Gibbons says. Strain sharing was highest in mother-child pairs, with 96 percent of them sharing strains, and only slightly lower in members of shared households, at 95 percent. And at least half of the mother-infant pairs shared 30 percent of their strains; the median was 12 percent among people in shared households. Yet, there was no sharing among eight percent of adult twins who lived separately, and 16 percent of people within villages who resided in different households. The results were published in Nature.
It’s not a regional phenomenon. Although the types of bacterial strains varied depending on whether people lived in western and eastern nations — datasets were drawn from 20 countries on five continents — the patterns of sharing were much the same. To establish these links, scientists focused on individual variations in shared bacterial strains, differences that create unique bacterial “fingerprints” in each person, while controlling for variables like diet, demonstrating that the bacteria had been transmitted between people and were not the result of environmental similarities.
The impact of this bacterial sharing isn’t clear, but shouldn’t be viewed with trepidation, according to Sean Gibbons, a microbiome scientist at the nonprofit Institute for Systems Biology.
“The vast majority of these bugs are actually either benign or beneficial to our health, and the fact that we're swapping and sharing them and that we can take someone else's strain and supplement or better diversify our own little garden is not necessarily a bad thing,” he says.
"There are hundreds of billions of dollars of investment capital moving into these microbiome therapeutic companies; bugs as drugs, so to speak,” says Sean Gibbons, a microbiome scientist at the Institute for Systems Biology.
Everyday habits like exercising and eating vegetables promote a healthy, balanced gut microbiome, which is linked to better metabolic and immune function, and fewer illnesses. While many people’s microbiomes contain bacteria like C. diff or E. coli, these bacteria don’t cause diseases in most cases because they’re present in low levels. But a microbiome that’s been wiped out by, say, antibiotics, may no longer keep these bacteria in check, allowing them to proliferate and make us sick.
“A big challenge in the microbiome field is being able to rationally predict whether, if you're exposed to a particular bug, it will stick in the context of your specific microbiome,” Gibbons says.
Gibbons predicts that explorations of microbe-based therapeutics will be “exploding” in the coming decades. “There are hundreds of billions of dollars of investment capital moving into these microbiome therapeutic companies; bugs as drugs, so to speak,” he says. Rather than taking a mass-marketed probiotic, a precise understanding of an individual’s microbiome could help target the introduction of just the right bacteria at just the right time to prevent or treat a particular illness.
Because the current study did not differentiate between different types of contact or relationships among household members sharing bacterial strains or determine the direction of transmission, Segata says his current project is examining children in daycare settings and tracking their microbiomes over time to understand the role genetics and everyday interactions play in the level of transmission that occurs.
This relatively newfound ability to trace bacterial variants to minute levels has unlocked the chance for scientists to untangle when and how bacteria leap from one microbiome to another. As researchers come to better understand the factors that permit a strain to establish itself within a microbiome, they could uncover new strategies to control these microbes, harnessing the makeup of each microbiome to help people to resist life-altering medical conditions.